Abstract
In Sect. 3.4 of Chap. 3, Bayes’ theorem is introduced in a setting of random events in a sample space. It is also shown how the theorem allows for the updating of the current knowledge about the probability of a certain event, in light of new information. In this context, the conditional probability arising from Bayes’ theorem is proportional to the inverse probability given by the theorem of total probability. This chapter explores Bayesian methods in more detail, with the aim of providing the reader with a basic overview of this important branch of statistics, which has extensive application opportunities in the modeling and inference of hydrologic random variables.
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Fernandes, W., Silva, A.T. (2017). Introduction to Bayesian Analysis of Hydrologic Variables. In: Naghettini, M. (eds) Fundamentals of Statistical Hydrology. Springer, Cham. https://doi.org/10.1007/978-3-319-43561-9_11
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